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Conventional screening is limited to a few cancer types, leaving nearly half of cancers without established programs. Multi-cancer early detection (MCED) tests based on circulating tumor biomarkers have shown promise, but sensitivity for early-stage remains a challenge. In parallel, detection of molecular residual disease (MRD) using circulating tumor DNA (ctDNA) has emerged as a powerful prognostic and predictive tool, though current assays remain limited in sensitivity and specificity. This study aims to integrate multi-omics data to develop more refined and highly sensitive MCED and MRD assays.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study leverages clinical information and biospecimens from patients with cancer and cancer-na\u00efve individuals. Samples from patients with cancers will be derived from the MONSTAR-SCREEN-3 study, while those from cancer-na\u00efve individuals will be obtained from the Tohoku Medical Megabank Project. Comprehensive analyses will include whole-genome sequencing (WGS), whole-exome sequencing (WES), whole-transcriptome sequencing (WTS), proteomics, metabolomics, and microbiome profiling using stool and saliva. Artificial intelligence (AI)-based multi-omics integration will be performed to develop novel MCED and MRD assays and to evaluate their clinical performance. The primary endpoints are the sensitivity and specificity of MCED and MRD assays.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This is the first large-scale study to integrate comprehensive multi-omics profiling with AI for MCED and MRD assay development. The findings are expected to advance precision oncology by improving early diagnosis and recurrence monitoring.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial registration<\/jats:title>\n                    <jats:p>UMIN000053815, approved by the Institutional Review Board of the National Cancer Center Hospital East.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s10147-026-03001-6","type":"journal-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T10:34:50Z","timestamp":1772793290000},"page":"843-850","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Clinical development of molecular residual disease (MRD) and multi-cancer early detection (MCED) using liquid biopsy multiomics with artificial intelligence (AI)"],"prefix":"10.1007","volume":"31","clinical-trial-number":[{"clinical-trial-number":"umin000053815","registry":"10.18810\/umin-japan"}],"author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7302-7691","authenticated-orcid":false,"given":"Taro","family":"Shibuki","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riu","family":"Yamashita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tadayoshi","family":"Hashimoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takao","family":"Fujisawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mitsuho","family":"Imai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junichiro","family":"Yuda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takeshi","family":"Kuwata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshihiro","family":"Misumi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshiaki","family":"Nakamura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hideaki","family":"Bando","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaname","family":"Kojima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayuri","family":"Tokioka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ippei","family":"Chiba","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naoki","family":"Nakaya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Hozawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seizo","family":"Koshiba","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nobuo","family":"Fuse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sakae","family":"Saito","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ritsuko","family":"Shimizu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Woong-Yang","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kengo","family":"Kinoshita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takayuki","family":"Yoshino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,6]]},"reference":[{"key":"3001_CR1","first-page":"17","volume":"73","author":"RL Siegel","year":"2023","unstructured":"Siegel RL, Miller KD, Wagle NS et al (2023) Cancer statistics, 2023. 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As the analysis incorporates data generated within the framework of the MONSTAR-SCREEN-3 study and ToMMo cohort, potential indirect associations arising from that context cannot be fully excluded. Here is that list: Shibuki T. reports honoraria from AstraZeneca and Novartis. Hashimoto T. reports honoraria from CytoGen and Takata Pharmaceutical. Fujisawa T. reports honoraria from Amelieff, AstraZeneca, and MSD outside the submitted work. Imai M. reports personal fees from Caris Life Sciences, Guardant Health, Inc., and Sumitomo Corp outside the submitted work. Misumi T. reports honoraria from Chugai and AstraZeneca. Junichiro Yuda: research funding from AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, BrighPath Bio, Celaid Therapeutics, Chugai, Daiichi Sankyo, Genmab, Incyte, Janssen Pharmaceutical, Mitsubishi Tanabe, MSD, Novartis, Sanofi, Sumitomo Pharma and Takeda Pharmaceutical. Nakamura N. reports personal fees from Guardant Health Pte, Ltd., Natera, Inc., Roche, Ltd., Premo Partners, Inc., Takeda Pharmaceutical, Exact Sciences Corporation, Gilead Sciences, Inc., MSD, Eisai Co., Ltd., Zeria Pharmaceutical Co., Ltd., Miyarisan Pharmaceutical Co., Ltd., Merck Biopharma Co., Ltd., CareNet, Inc., Hisamitsu Pharmaceutical Co., Inc., Taiho Pharmaceutical Co., Ltd., Becton, Dickinson and Company, and Guardant Health Japan Corp.; grants and personal fees from Seagen, Inc., Daiichi Sankyo Co., Ltd., and Chugai Pharmaceutical Co., Ltd.; as well as grants from Genomedia Inc., Guardant Health AMEA, Inc., Guardant Health, Inc., Tempus Labs, Inc., and Roche Diagnostics K.K. outside the submitted work. Bando H. reports personal fees from Ono Pharmaceutical, Taiho Pharmaceutical, and Eli Lilly Japan K. K. outside the submitted work. Yoshino T. reports personal fees from Chugai Pharmaceutical Co. Ltd., Takeda Pharmaceutical, Merck Biopharma Co. Ltd., Bayer Yakuhin, Ono Pharmaceutical, MSD, and Sumitomo Corp, as well as grants from Amgen, Chugai Pharmaceutical, Daiichi Sankyo, Eisai Co. Ltd., FALCO Biosystems, Genomedia, Molecular Health, MSD, Nippon Boehringer Ingelheim Co., Ltd., Ono Pharmaceutical, Pfizer, Roche Diagnostics, Sanofi, Sysmex, and Taiho Pharmaceutical outside the submitted work. The other authors have no competing interests to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The research protocol was reviewed and approved by the Institutional Review Boards of the National Cancer Center Hospital East and ToMMo (approval number: 2023\u2013349). All procedures were carried out in accordance with the principles of the Declaration of Helsinki and with Japan\u2019s Ethical Guidelines for Medical and Health Research Involving Human Subjects. Prospective participants who provided blood samples for ctDNA analysis gave written informed consent prior to enrollment. For studies using archived data, the Institutional Review Boards granted a waiver of informed consent in accordance with national regulations.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Written informed consent, including consent for publication, was obtained from participants who provided new biospecimens prospectively. For participants whose existing data and samples were used retrospectively, consent was waived under an opt-out process approved by the institutional review boards. All data will be presented in a manner that precludes individual identification.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}